Title :
Particle swarm with extended memory for multiobjective optimization
Author :
Hu, Xiaohui ; Eberhart, Russell C. ; Shi, Yuhui
Author_Institution :
Dept. of Biomed. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
This paper presents a modified dynamic neighborhood particle swarm optimization (DNPSO) algorithm for multiobjective optimization problems. PSO is modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple objectives. An extended memory is introduced to store global Pareto optimal solutions to reduce computation time. Several benchmark cases were tested and the results show that the modified DNPSO is much more efficient than the original DNPSO and other multiobjective optimization techniques.
Keywords :
Pareto optimisation; evolutionary computation; search problems; DNPSO algorithm; computation time; dynamic neighborhood particle swarm optimization; extended memory; global Pareto optimal solutions; multiobjective optimization problems; one-dimension optimization; particle memory updating; Benchmark testing; Biomedical engineering; Equations; Evolutionary computation; Optimization methods; Particle swarm optimization; Random number generation; Stochastic processes;
Conference_Titel :
Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of the 2003 IEEE
Print_ISBN :
0-7803-7914-4
DOI :
10.1109/SIS.2003.1202267
